Middle age is a critical period for cardio-metabolic diseases, including coronary artery disease, hypertension and type 2 diabetes. The importance of impact of childhood adverse growth experience on adult cardio-metabolic diseases has long been recognized. Telomere length and DNA methylation (DNAm) age are highly correlated with chronological age and considered as biomarkers of human aging. Recent studies have clarified that changes in telomere length and DNAm predict cardio-metabolic disease, atherosclerosis and mortality. Despite extensive studies on the early origins of cardio-metabolic disease and biological aging, the combined effect of prenatal experience, early life developmental patterns and cardio-metabolic aging process is not well understood and remains an important research area. This secondary data analysis proposal is directed to the following Specific Aims: 1) To examine the impact of early life growth trajectory patterns on telomere age, DNAm age and cardio-metabolic disease in middle-aged black and white adults; 2) To investigate the temporal relationship of BMI-telomere and BMI-DNAm and the effect of their temporal sequence patterns on adult cardio-metabolic disease; 3) To determine the mediation effect of telomere and DNAm aging biomarkers on the association of early life growth and risk burden with adult cardio-metabolic risk; 4) To examine whether race, gender and birth weight modify the association and mediation effect parameters. The cardio-metabolic outcomes include hypertension, type 2 diabetes, coronary artery disease and subclinical cardiovascular measures. Telomere length and DNAm age will be used as mediators. The specific aims will be achieved by leveraging the existing longitudinal cohort of the Bogalusa Heart Study followed from childhood since 1973. We propose to analyze two cohorts: a longitudinal cohort of 3,627 adults (2,285 whites and 1,342 blacks), aged 28-61 years, who have height, body mass index (BMI), skin folds measured 3-9 times in childhood and 2-6 times in adulthood, and a sub-cohort of 1,168 adults (747 whites and 421 blacks) who also have telomere data and genome-wide 450K DNAm profiles measured at two time-points 5-12 years apart in adulthood. Cross-lagged models for temporal relationship analysis, mediation analysis models, regression models and interaction analysis models will be performed. Findings on the impact of early life growth on cardio-metabolic disease in relation to biological aging markers will facilitate identification of high risk individuals and selection of novel therapeutic and intervention strategies in early life.